Vascular segmentation and feature identification is a preliminary stage of image-based measurement of vascular state. Though many stages of vascular segmentation and feature identification can be performed based primarily on automated analysis, relevant image features are often of low contrast and/or embedded in a complex environment comprising elements of ambiguous geometry and extraneous features. Human supervision may be introduced into the workflow to make corrections and help ensure quality of results, resulting in a semi-automated process, for example as in the Livewire and related procedures (discussed, for example, in Ryan Dickie, et al.; Live-vessel: Interactive vascular image segmentation with simultaneous extraction of optimal medial and boundary paths. Technical report TR 2009-23, School of Computing Science, Simon Fraser University, Burnaby, BC, Canada, November 2009).
Additional background art includes:
an article titled: “Snakes: Active contour models”, by M. Kass, A. Witkin, and D. Terzopoulos, published in Int. J. Comput. Vis. (1987), 1:321-331;
an article titled: “Multiscale vessel enhancement filtering”, by A. F Frangi, W. J. Niessen, K. L. Vincken, M. A. Viergever, published in Medical Image Computing and Computer-Assisted Intervention-MICCA '98; and
an article titled: “Snakes, Shapes, and Gradient Vector Flow”, by C. Xu and J. L. Prince, published in IEEE Transactions on Image Processing (1998), 7:359-369.